@inproceedings{4a3214a9f0d647959b6e7d3fc3e3e2df,
title = "Ensemble selection for evolutionary learning using information theory and Price's theorem",
abstract = "This paper presents an information theoretic perspective on design and analysis of evolutionary algorithms. Indicators of solution quality are developed and applied not only to individuals but also to ensembles, thereby ensuring information diversity. Price's Theorem is extended to show how joint indicators can drive reproductive sampling rate of potential parental pairings. Heritability of mutual information is identified as a key issue.",
keywords = "Ensemble models, Evolutionary computation, Group selection, Machine learning, Mate selection, Price's Equation",
author = "Card, {Stuart W.} and Mohan, {Chilukuri K.}",
note = "Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 8th Annual Genetic and Evolutionary Computation Conference 2006 ; Conference date: 08-07-2006 Through 12-07-2006",
year = "2006",
doi = "10.1145/1143997.1144254",
language = "English (US)",
isbn = "1595931864",
series = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
publisher = "Association for Computing Machinery (ACM)",
pages = "1587--1588",
booktitle = "GECCO 2006 - Genetic and Evolutionary Computation Conference",
address = "United States",
}